Background: Nigella sativa or black seed extract has been reported to show various medicinal benefits. Thymoquinone which is an active compound of its seed has been reported to contain anti-cancer properties.
Objective: The study addressed the anti-cancer efficiency of long-term in vitro treatment with thymoquinone towards human breast cancer cell lines MCF-7.
Materials And Methods: Cell proliferation was determined with CellTiter 96 Aqueous. Non-Radioactive Cell Proliferation Assay Kit. It was followed with trypan blue exclusion test to determine the percentage of viable cells. The study incorporated cell cycle assay to distinguish cell distribution at various cell cycle phases using Cycletest Plus DNA Reagent Kit. The apoptosis detection kit was used to determine the percentage of apoptotic and necrotic cells using flow cytometry.
Results: The 50% inhibitory concentration (IC50) value determined using the proliferation assay was 25 μM thymoquinone. Late apoptotic cell percentage increased rapidly when treatment duration was increased to 24 h with 25 and 100 μM thymoquinone. Further analysis using cell cycle assay showed thymoquinone inhibition of breast cancer cell proliferation at minimal dose 25 μM and led to S phase arrest significantly at 72 h treatment (P = 0.009). It was also noted elevation sub-G1 peak following treatment with 25 μM thymoquinone for 12 h. Increase in thymoquinone to 50 μM caused G2 phase arrest at each time-point studied.
Conclusion: In general thymoquinone showed sustained inhibition of breast cancer cell proliferation with long-term treatment. Specificity of phase arrest was determined by thymoquinone dose.
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http://dx.doi.org/10.4103/0974-8490.112428 | DOI Listing |
Pharm Dev Technol
January 2025
Department of Pharmacy, School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, China.
In this paper, the pH-sensitive targeting functional material NGR-poly(2-ethyl-2-oxazoline)-cholesteryl methyl carbonate (NGR-PEtOz-CHMC, NPC) modified quercetin (QUE) liposomes (NPC-QUE-L) was constructed. The structure of NPC was confirmed by infrared spectroscopy (IR) and nuclear magnetic resonance hydrogen spectrum (H-NMR). Pharmacokinetic results showed that the accumulation of QUE in plasma of the NPC-QUE-L group was 1.
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFInt J Gen Med
December 2024
Department of Thyroid and Breast Surgery, Quzhou People's Hospital, Quzhou, 324000, People's Republic of China.
Objective: This study aims to demonstrate the impact of sarcopenia on the prognosis of early breast cancer and its role in early multimodal intervention.
Methods: The clinical data of patients (n=285) subjected to chemotherapy for early-stage breast cancer diagnosed pathologically between January 1, 2016, and December 31, 2020, in our hospital were retrospectively analyzed. Accordingly, the recruited subjects were divided into sarcopenia (n=85) and non-sarcopenia (n=200) groups according to CT diagnosis correlating with single-factor and multifactorial logistic regression analyses.
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